Adrian Zlocki

euroFOT: Field Operational Test and Impact Assessment of Advanced Driver Assistance Systems: Final Results

Within the first European large scale field operational test euroFOT the effects of eight different Advanced Driver Assistance Systems (ADAS) were investigated. About 1,000 vehicles equipped with different ADAS were used. The Institute of Automotive Engineering (ika) of the RWTH Aachen University analysed the effects of ACC usage in combination with FCW under normal driving conditions of 100 passenger cars. The results of the data analysis show positive effects on traffic safety and fuel consumption. In addition, the complete process chain from the data collection to the analysis was defined and conducted at the ika.

Evaluation and Sign-Off Methodology for Automated Vehicle Systems Based on Relevant Driving Situations

Automated driving is currently under research in various projects and research activities. These activities are clustered in different research areas. The evaluation and sign-off methodology for automated vehicles is currently a challenge to be solved. An innovative approach for such a sign-off methodology is proposed. A state-of-the-art overview of existing evaluation methods for advanced driver assistance systems, which are already available on the market today, is given in the form of a systems engineering process model. The existing evaluation methods already require great effort for real-world testing. Applying these methods to automated vehicles will exceed reasonable budget and time. The proposed method for effective evaluation of automated vehicles considers a database of relevant driving situations, which are collected and simulated on the basis of accident data and field operational and dedicated studies under controlled conditions. The database of relevant driving situations is the basis for an effective evaluation to be applied in simulation, driving simulators, and in test track scenarios. The methodology is described, and necessary building blocks are provided to implement the proposed concept.

Effects of ACC and FCW on Speed, Fuel Consumption, and Driving Safety

Intelligent Transportation Systems (ITS) are widely expected to deliver a major contribution to the improvement of driving comfort as well as road safety. An insight into the benefits of ITS is an important ingredient in the deployment of ITS. Assessing these benefits is one of the research goals within the 7th Framework Program of the European Commission. Field Operational Tests (FOT) have emerged as an important research methodology for assessing the impact of ITS on driver behavior and performance, traffic safety, traffic efficiency as well as the environment. Within the euroFOT project, a large scale field test that involves approximately 1000 instrumented vehicles on the road all over Europe the impact of eight selected ITS function is tested. Most of these vehicles have one or more ITS applications on board, including continuously operating ones like Adaptive Cruise Control (ACC) and Forward Collision Warning (FCW). This paper describes the method applied for the FOT to assess the impact of the ACC and FCW. The euroFOT approach has some similarities to existing FOTs but includes novel aspects to handle specific limitations and conditions of the FOT and the available data. The paper further describes the final results of the data analysis based on the predefined hypotheses to answer the research questions of the project.

Technical Evaluation and Impact Assessment of Automated Driving

Currently different research activities on automated driving are conducted around the globe. The European flagship research project on automated driving functions is the research project “AdaptIVe” (Automated Driving Applications and Technologies for Intelligent Vehicles). Besides the development of automated driving functions, the project deals with general research on legal aspects, human factors and evaluation. The evaluation and impact assessment of automated driving functions faces different challenges considering the complexity of the technology. In this context, this paper describes the evaluation approaches that are taken in the project for the technical evaluation and impact assessment.

Evaluation of Automated Road Vehicles

In the past years various partially automated driving functions have been introduced on the market. More advanced functions are currently in research. By means of these functions partly automated driving in specific driving situations is already realized, e.g. a traffic jam assist performs longitudinal and lateral control at low speeds. Besides the technical challenges to realize automated driving in complex driving situations, e.g. intersection areas, new approaches to evaluate these functions under different driving conditions are necessary, in order to assess the benefits and identify potential weaknesses. In this context, this chapter describes a systematic approach to evaluate road vehicles with automated driving functions. The presented approach is divided into a technical, a user-related and an impact evaluation.

A-priori map information and path planning for automated valet-parking

Automated valet parking can help manage space in parking garages more efficiently and increase the comfort for the driver by delegating the parking task to the system. To successfully navigate the vehicle in a parking garage, the valet parking system requires a-priori information about the environment. This paper shows an approach to derive a-priori information from available blueprints of a parking lot. Based on the derived map data, paths for Ackermann-steered vehicles are planned to navigate vehicles through the parking area and park them into desired parking spots.

Concept of an enhanced V2X pedestrian collision avoidance system with a cost function–based pedestrian model

ABSTRACT Objective: State-of-the-art collision avoidance and collision mitigation systems predict the behavior of pedestrians based on trivial models that assume a constant acceleration or velocity. New sources of sensor information—for example, smart devices such as smartphones, tablets, smartwatches, etc.—can support enhanced pedestrian behavior models. The objective of this article is the development and implementation of a V2Xpedestrian collision avoidance system that uses new information sources. Methods: A literature review of existing state-of-the-art pedestrian collision avoidance systems, pedestrian behavior models in advanced driver assistance systems (ADAS), and traffic simulations is conducted together with an analysis of existing studies on typical pedestrian patterns in traffic. Based on this analysis, possible parameters for predicting pedestrian behavior were investigated. The results led to new requirements from which a concept was developed and implemented. Results: The analysis of typical pedestrian behavior patterns in traffic situations showed the complexity of predicting pedestrian behavior. Requirements for an improved behavior prediction were derived. A concept for a V2X collision avoidance system, based on a cost function that predicts pedestrian near future presence, and its implementation is presented. The concept presented considers several challenges such as information privacy, inaccuracies of the localization, and inaccuracies of the prediction. Conclusion: A concept for an enhanced V2X pedestrian collision avoidance system was developed and introduced. The concept uses new information sources such as smart devices to improve the prediction of the pedestrians presence in the near future and considers challenges that come along with the usage of these information sources.

Data Management and Data Sharing in Field Operational Tests

In this chapter it will be discussed how data from Field Operational Tests of Intelligent Transport Systems can be managed and shared. The Field Operational Tests, where hundreds of users get to experience the latest systems, aim to assess the impacts that would result from a wide-scale implementation. Evaluation principles of Field Operational Tests will be explained, and a closer look will be taken at the data that is collected for carrying out the assessments. The widely used FESTA methodology for designing and conducting Field Operational Tests and Naturalistic Driving Studies already provides several recommendations for managing data. This methodology will be discussed and illustrated by examples of its use in European projects. As field test projects set out to collect a huge set of data, the projects themselves do not usually have the scope or the resources to analyze the data from every perspective. Therefore re-use of the collected data also by other projects with different research questions has the potential to generate a wealth of new knowledge about what is happening in the interactions between drivers, vehicles and the infrastructure. Data sharing is the focus of a European support action, FOT-Net Data. The support action is working, with international collaboration, to form a data sharing framework, a data catalogue, and provide detailed recommendations for *Corresponding author: Y.Barnard@leeds.ac.uk 60 Intelligent Transportation Systems: From Good Practices to Standards sharing and re-use. Outcomes from this activity will be discussed. Ways of sharing different types of data will be described, including the necessary steps to be taken to open up the data.

Sensitivity analysis for model based fusion of camera systems with navigation data

Current advanced driver assistance systems (ADAS) for lateral support are based on optical sensors for environmental detection. Due to different influences e.g. bad sight conditions or missing lane markings, theses systems might not be able determine the necessary information. In order to improve the availability and reliability of camera based ADAS systems in these situations, the potential of a fusion with navigation information is analyzed at the Institut für Kraftfahrzeuge (ika) RWTH Aachen University. Therefore, a fusion model is developed, which continuously fuses data between a camera system with vehicle inertial data and navigation information. In order to gain optimal results out of the fusion model, different sources of potential errors, which have a negative influence on precision, are identified and analyzed within a sensitivity analysis.

Wirkungsanalyse von Abstandsregelung und Abstandswarnung

Im Rahmen des ersten europaischen Feldversuchs euroFOT wurde die Wirkung von acht verschiedenen Fahrerassistenzsystemen im offentlichen Strasenverkehr untersucht. Neben der Umsetzung der kompletten Prozesskette zur Datenerhebung und -verarbeitung wurde am Institut fur Kraftfahrzeuge der RWTH Aachen University eine Wirkungsanalyse fur die Abstandsregelung (Adaptive Cruise Control, ACC) und die Abstandswarnung (Forward Collision Warning, FCW) an 100 Pkw durchgefuhrt. Die Ergebnisse der Wirkungsanalyse zeigen positive Effekte auf die Verkehrssicherheit und den Kraftstoffverbrauch.